The rise of large-scale AI models capable of processing diverse modalities like text and images presents a unique infrastructural challenge. These models require immense computational power and specialized hardware to efficiently handle training, fine-tuning, and inference. Over a decade ago, Google began developing custom AI accelerators, Tensor Processing Units (TPUs), to address the growing demands of AI workloads, paving the way for multimodal AI. Earlier this year, we announced Trillium, ou...